@InProceedings{vanderwees-bisazza-monz:2016:WNUT,
  author    = {van der Wees, Marlies  and  Bisazza, Arianna  and  Monz, Christof},
  title     = {A Simple but Effective Approach to Improve Arabizi-to-English Statistical Machine Translation},
  booktitle = {Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {43--50},
  abstract  = {A major challenge for statistical machine translation (SMT) of
	Arabic-to-English user-generated text is the prevalence of text written in
	Arabizi, or Romanized Arabic. When facing such texts, a translation system
	trained on conventional Arabic-English data will suffer from extremely low
	model coverage. In addition, Arabizi is not regulated by any official
	standardization and therefore highly ambiguous, which prevents rule-based
	approaches from achieving good translation results. In this paper, we improve
	Arabizi-to-English machine translation by presenting a simple but effective
	Arabizi-to-Arabic transliteration pipeline that does not require knowledge by
	experts or native Arabic speakers. We incorporate this pipeline into a
	phrase-based SMT system, and show that translation quality after automatically
	transliterating Arabizi to Arabic yields results that are comparable to those
	achieved after human transliteration.},
  url       = {http://aclweb.org/anthology/W16-3908}
}